From the 1 of 4 linked papers with an AI index.
4 papers
ThinkLog: Leveraging Reasoning for Log Statement Generation
Kazuki Kusama, Honglin Shu, Masanari Kondo +2
ThinkLog uses large language models with reasoning prompts to automatically decide where to insert logs, what severity to assign, and how to phrase log messages, improving the accu…
Leveraging Language Models for Log Statement Generation in Multilingual Scenarios: How Far Are We?
Kazuki Kusama, Honglin Shu, Masanari Kondo +1
Log statements capture critical information for software maintenance activities such as testing, debugging, and failure analysis. Because of this importance, developers must carefu…
Why Are Agentic Pull Requests Merged or Rejected? An Empirical Study
Sien Reeve O. Peralta, Fumika Hoshi, Hironori Washizaki +8
AI coding agents increasingly submit pull requests (Agentic-PRs) to open-source repositories, yet their performance is commonly assessed using merge and rejection outcomes alone. W…
How Small is Enough? Empirical Evidence of Quantized Small Language Models for Automated Program Repair
Kazuki Kusama, Honglin Shu, Masanari Kondo +1
Background: Large language models (LLMs) have greatly improved the accuracy of automated program repair (APR) methods. However, LLMs are constrained by high computational resource…